Whether you want to do business analytics or build the deep learning models, getting correct data and cleansing it appropriately remains the major task. Find out experts opinions on how you can make efficient data cleansing and collection efforts.

Work closely with the Director to develop, manage, and maintain various data-driven processes and applications, including reporting and analysis, data integrity and security to support Columbia College and its units.

Our path-breaking platform brings real-time machine learning and graph analytics capabilities to the blockchain, and pragmatic and data-driven solutions to the worlds of payments, financial services and the Internet of Things.

This book takes a data mining perspective to offer an overview of studying human mobility in location-based social networks (LBSN) and illuminate a wide range of related computational tasks. It also highlights what are the unique characteristics and research opportunities of LBSN data.

CRN identifies Top 10 startups which offer the coolest technology in big data. The list includes companies which focus on business intelligence, business & visual Analytics, Hadoop technology and cloud-based systems.

The Internet of Things (IoT) is the next technological revolution, expected to generate over $300 B by year 2020, according to Gartner. The IoT will also generate unprecedented amounts of data and its impact will be felt across the entire big data universe.

Google's DeepDream project has gone viral which allows to visualize the deep learning neural networks. It highlights a need for a generalized algorithm visualization tool, in this post we introduce to you one such effort.

In a thriving analytic practice, the role of a data scientist is not defined by a person, but by a team. Within that team, several roles may be filled by one person-and several people may fulfill a given role.

With big data about energy usage at the device level, enterprises are reducing consumption, optimizing processes for efficiency, and creating sustainability initiatives that advance them in economic, social, and environmental realms.

CIKM 2015 competition is focused on Australian Football league (AFL), and predicting outcomes of future AFL matches using machine learning techniques based on historical data on teams, players and their performances.

Here, find out how leading analysts and researchers are exploring the sentiment analysis and text mining in their areas. Also, explore the opportunities, challenges and use-cases for the sentiment analysis.

Top Stanford researchers teach efficient and scalable methods for extracting models and other information from very large amounts of data. Next session of this great course starts Sep 12 on Coursera and is free.

Prof. Jian Pei wins ACM SIGKDD 2015 Service Award for his significant technical contributions to the principles, practice and application of data mining and for his outstanding services to society and the data mining community.

Find out how KNIME allows us to integrating analytical languages, such as R and Python and visual design of SQL code. Also, learn to integrate your Hadoop, visualization and ETL systems with the KNIME.

ArXiv.org gives researchers the ability to instantly publish research, free of peer review and the publication cycle. This capability offers both advantages and pitfalls. We should warily eye the 24-7 news cycle as a cautionary tale for how this could go wrong.

This collection investigate the principles and methodologies of mining latent entity structures from massive unstructured and interconnected data. We propose a text-rich information network model for modeling data in many different domains.

Provide reliable and timely high-level qualitative and quantitative data and trend analysis that supports the strategic planning and operational effectiveness of key Vice Chancellor for Research programs.

One aspect of BI self-service modules is the flexibility for the user to define his own story line and the order in which the user wants to see the visuals. Find out how you can build the rearrangeable dashboards.

The IEEE ICDM awards recognize influential research contributions to the field of data mining, and major service contributions that have promoted data mining as a field and ICDM as the world premier research conference. Nominations due Aug 15.

We discuss the role of Analytics at Groupon, deciding factors for merchant priority, limitations of historical data, optimizing the efforts of sales force, data characteristics and dealing with Data Sparsity.

Data science is nothing but the old wine in new bottle versions of the statistics with different fields. Here, we are busting the myth which states data scientist is new and different than traditional statisticians.

Developer with a strong analytical background and excellent programming skills to collaborate with a team developing new machine learning algorithms for NLP, text classification, sentiment analysis, and similar tasks.

Google scientist clarifies misconceptions and myths around Deep Learning Adversarial Examples, including: they do not occur in practice, Deep Learning is more vulnerable to them, they can be easily solved, and human brains make similar mistakes.

This free book is an easy to digest introduction to the world of predictive analytics and Big Data. The book is written from a policing perspective and shows interesting views in how the power of the police force can be increased by focusing on predictive policing.